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Optimization of Crystal Growth for Neutron Macromolecular Crystallography
Author(s) -
Elham Vahdatahar,
Niels Junius,
Monika Budayova-Spano
Publication year - 2021
Publication title -
journal of visualized experiments
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.596
H-Index - 91
ISSN - 1940-087X
DOI - 10.3791/61685
Subject(s) - crystallization , crystal (programming language) , neutron , phase problem , crystallography , crystal growth , phase (matter) , microscope , materials science , diffraction , neutron diffraction , biological system , computer science , chemistry , physics , crystal structure , optics , biology , thermodynamics , nuclear physics , organic chemistry , programming language
The use of neutron macromolecular crystallography (NMX) is expanding rapidly with most structures determined in the last decade thanks to new NMX beamlines having been built and increased availability of structure refinement software. However, the neutron sources currently available for NMX are significantly weaker than equivalent sources for X-ray crystallography. Despite advances in this field, significantly larger crystals will always be required for neutron diffraction studies, particularly with the tendency to study ever-larger macromolecules and complexes. Further improvements in methods and instrumentation suited to growing larger crystals are therefore necessary for the use of NMX to expand. In this work, we introduce rational strategies and a crystal growth bench (OptiCrys) developed in our laboratory that combines real-time observation through a microscope-mounted video camera with precise automated control of crystallization solutions (e.g., precipitant concentration, pH, additive, temperature). We then demonstrate how this control of temperature and chemical composition facilitates the search for optimal crystallization conditions using model soluble proteins. Thorough knowledge of the crystallization phase diagram is crucial for selecting the starting position and the kinetic path for any crystallization experiment. We show how a rational approach can control the size and number of crystals generated based on knowledge of multidimensional phase diagrams.

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